Evidence map›Paper›PMID 32751059›Full record

ArticleBiomedicines2020

Highlighting Human Enzymes Active in Different Metabolic Pathways and Diseases: The Case Study of EC 1.2.3.1 and EC 2.3.1.9.

Giulia Babbi, Davide Baldazzi, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 46% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. From Catalysis of Evolution to Evolution of Catalysis.Accounts of chemical research · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Giulia BabbiBiocomputing Group, University of Bologna, 40126 Bologna, Italy.ORCID 0000-0002-9816-4737
Davide BaldazziBiocomputing Group, University of Bologna, 40126 Bologna, Italy.
Castrense SavojardoBiocomputing Group, University of Bologna, 40126 Bologna, Italy.ORCID 0000-0002-7359-0633
Pier Luigi MartelliBiocomputing Group, University of Bologna, 40126 Bologna, Italy.
Rita CasadioBiocomputing Group, University of Bologna, 40126 Bologna, Italy.ORCID 0000-0002-7462-7039
University of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enzymes are key proteins performing the basic functional activities in cells. In humans, enzymes can be also responsible for diseases, and the molecular mechanisms underlying the genotype to phenotype relationship are under investigation for diagnosis and medical care. Here, we focus on highlighting enzymes that are active in different metabolic pathways and become relevant hubs in protein interaction networks. We perform a statistics to derive our present knowledge on human metabolic pathways (the Kyoto Encyclopaedia of Genes and Genomes (KEGG)), and we found that activity aldehyde dehydrogenase (NAD(+)), described by Enzyme Commission number EC 1.2.1.3, and activity acetyl-CoA C-acetyltransferase (EC 2.3.1.9) are the ones most frequently involved. By associating functional activities (EC numbers) to enzyme proteins, we found the proteins most frequently involved in metabolic pathways. With our analysis, we found that these proteins are endowed with the highest numbers of interaction partners when compared to all the enzymes in the pathways and with the highest numbers of predicted interaction sites. As specific enzyme protein test cases, we focus on Alpha-Aminoadipic Semialdehyde Dehydrogenase (ALDH7A1, EC 2.3.1.9) and Acetyl-CoA acetyltransferase, cytosolic and mitochondrial (gene products of ACAT2 and ACAT1, respectively; EC 2.3.1.9). With computational approaches we show that it is possible, by starting from the enzyme structure, to highlight clues of their multiple roles in different pathways and of putative mechanisms promoting the association of genes to disease.

Indexed as

enzymesKEGG pathways KEGG metabolic pathwaysprotein-protein interactionprotein stabilityprotein variation

Identifiers

PMID32751059
PMCPMC7459455
OpenAlexW3045593773

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.